Tumor characteristics impact prognosis in deficient mismatch repair/microsatellite instability-high localized colorectal cancer—a systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Deficient mismatch repair (dMMR) and microsatellite instability-high (MSI-H) tumors constitute ∼15% of localized colorectal cancers (CRCs). Prognostic biomarkers such as tumor-infiltrating lymphocytes (TILs) and BRAF and KRAS mutations may guide personalized treatment for these patients, and this systematic review and meta-analysis aimed to evaluate their impact on survival outcomes. METHODS: Literature searches were conducted across PubMed, Embase, Cochrane Library, and Web of Science, including studies published between 2004 and 2023. The primary outcomes were overall survival (OS), disease-free survival (DFS), and cancer-specific survival. The risk of bias was assessed using the Newcastle-Ottawa Scale, and the certainty of evidence using the GRADE approach. RESULTS: The literature search yielded 5636 articles. Fifty-four studies were included in the systematic review and 31 studies in the meta-analysis, totaling 4551 patients. High TIL density was significantly associated with improved OS (hazard ratio [HR] = 0.39, 95% CI = 0.17 to 0.89) and DFS (HR = 0.45, 95% CI = 0.29 to 0.71). BRAF and KRAS mutations were seen in 52% and 34% of patients, respectively, and were associated with poorer OS (HR = 1.43, 95% CI = 1.13 to 1.80 and HR = 1.30, 95% CI = 1.09 to 1.54, respectively). Quality of evidence was moderate to high across all exposures and outcomes. CONCLUSION: High infiltration of TILs correlated with improved OS and DFS, whereas BRAF and KRAS mutations were associated with worse OS in patients with localized dMMR/MSI-H CRC. These findings highlight the potential utility of biomarkers for improving prognostic assessment and personalizing management in dMMR CRC.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.005 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it